Autonomous Truck Control Modeling With 3D Roadway Simulation
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Solution Overview
Problem
Existing autonomous vehicle control systems developed for passenger vehicles are inadequate for larger, more complex vehicles like cargo trucks, as they fail to account for the additional road information needed due to the vehicle's size, weight, and varying cargo loads, leading to unpredictable performance.
Innovation Solution
A method and system that utilizes 3-dimensional roadway data to develop and optimize a generic vehicle control algorithm through computer simulations, allowing for real-world testing without needing to revise the algorithm, focusing on modifying the vehicle computer model to achieve acceptable performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If 2-dimensional road maps are used for autonomous vehicle control, then the system is simple and works well for passenger vehicles, but it provides unacceptable results for larger cargo vehicles
Solution Approach 1:
The patent transitions from using 2-dimensional road maps to 3-dimensional roadway data that includes elevation information. This dimensional change allows the control system to account for grade changes and terrain variations that significantly affect the performance of large cargo vehicles, thereby improving reliability without excessive complexity increase.
2Productivity
If generic control algorithms are developed without vehicle-specific parameters, then development is faster and easier, but performance becomes unpredictable for different vehicle types
Solution Approach 1:
The patent performs computer simulations before real-world testing to predict vehicle performance. By simulating the autonomous vehicle's behavior on 3-dimensional roadway data with vehicle-specific parameters (weight, dimensions, power-to-weight ratio) beforehand, the system can optimize control algorithms and identify potential issues before deployment, ensuring predictable performance while maintaining efficient development.
3Measurement precision
If vehicle-specific parameters are incorporated into simulations, then control accuracy improves for large vehicles, but the modeling process becomes more complex
Solution Approach 1:
The patent incorporates vehicle-specific parameters (weight, dimensions, power-to-weight ratio, cargo configuration) into the simulation model to accurately represent the physical characteristics of large cargo vehicles. These parameter changes enable precise prediction of vehicle performance on varied terrain, allowing the control system to be optimized for specific vehicle types while managing model complexity through systematic parameter integration.
Data Source
AI summary
The system and method make it feasible to develop an autonomous vehicle control system for complex vehicles, such as for cargo trucks and other large payload vehicles. The method and system commence by first obtaining 3-dimensional data for one or more sections of roadway. Once the 3-dimensional roadway data is obtained, that data is used to run computer simulations of a computer model of a specific vehicle being controlled by a generic vehicle control algorithm or system. The generic vehicle control algorithm is optimized by running the simulations utilizing the 3-dimensional roadway data until an acceptable performance result is achieved. Once an acceptable simulation is executed using the generic vehicle control algorithm, the control algorithm/system is used to run one or more real-world driving tests on the roadway for which the 3-dimensional data was obtained. Finally, the computer model for the vehicle is modified.